Methodology v1.0 · April 2026

How we rank AI use cases — without a black box.

The Industry AI Use Case Finder ranks 8+ use cases per industry against your seven wizard answers. The engine is rule-based, deterministic, and open. No LLM call sits in the ranking path. The weights below are the entire model.

Principles

Three commitments behind every ranking.

  • Determinism

    Two users with identical answers always see the same ranking.

    There is no LLM in the ranking path. Inputs map deterministically to scores and the score table is auditable on this page.

  • Transparency

    The weights table below is the entire ranking model.

    No hidden tiers, no editorial nudges, no commission-driven boosts. If you spot a use case that should rank differently, the weights tell you exactly why it does.

  • Recency

    Every use case carries a year-tagged citation.

    We refresh the catalog quarterly. ROI bands scale by company size and convert to local currency via a static FX table refreshed monthly.

Scoring

The weights table is the model.

Each use case in the catalog is scored against the seven wizard answers. The base signals are pain-point overlap, budget fit, time-to-value vs. timeline, current AI maturity, top concern, and recency of customer evidence. Top 8 are returned; lower-ranked items are kept with their score so any audit can replay the decision.

RuleWeightNote
Pain-point overlap+30 eachUp to 2 user-selected pain points; this is the strongest signal in ranking.
Budget supports use case+15Soft bonus when the user’s budget meets the use case minimum.
Budget below minimum−50Hard penalty — keeps unaffordable items out of the top 8.
Time-to-value fits timeline+10Aligns recommendations with the user’s declared horizon.
Concern-aligned bonuses+5 to +15Cost / employees / data security / vendor trust / where-to-start / quality.
AI maturity gap too large−25Applied when no current AI usage but use case requires advanced maturity.
Recency / customer evidence+5Boost when at least one year-tagged citation is on the use case.

ROI scaling

Per-use-case ROI bands are advisory and refreshed quarterly. They scale by company size — 0.3× for 1–10 employees up to 2.5× for 1,000+ — and convert to local currency via a static FX table refreshed monthly. ROI is not a guarantee.

Lead score

We also score each submission for sales routing: 200+ employees, $100K+ budget, near-term timeline, ICP industry, high-effort top use case, and concerns that signal buying readiness. The score determines whether a discovery call is offered or a long-tail nurture sequence runs.

Data sources

Where the numbers come from.

ROI ranges blend public benchmarks with anonymised buzzi.ai customer projects. Every use case carries at least one year-tagged citation. We refresh the catalog quarterly; the changelog below is the source of truth.

  • McKinsey AI Quarterly
  • Deloitte State of AI in the Enterprise (annual)
  • KPMG AI Pulse (quarterly)
  • Industry trade reports (NAR, NRA, ABA, AAFP, IndustryWeek, and more)
  • buzzi.ai customer projects (anonymised, validated)
  • Vendor-published case studies (year-tagged only)

Versioning

v1.0 — April 2026.

Refreshed quarterly. Every change to the catalog or the weights table is logged on this page. Subscribe to the buzzi.ai changelog to be notified when v1.1 ships.

Disclaimers

What this tool is, and isn’t.

ROI ranges are advisory; this is not financial advice. Currency conversions use a static FX table refreshed monthly. The tool helps you choose where to invest, not how much. We do not take commissions on any vendor recommended by the catalog.

Ready to rank yours?

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Seven questions, sixty seconds, eight ranked use cases. Free, board-ready PDF included.

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